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Knowledge Extraction and Applications utilizing Context Data in Knowledge Graphs

: Dörpinghaus, Jens; Stefan, Andreas


Ganzha, M. ; Institute of Electrical and Electronics Engineers -IEEE-:
Federated Conference on Computer Science and Information Systems, FedCSIS 2019. Proceedings : September 1-4, 2019, Leipzig, Germany
Piscataway, NJ: IEEE, 2019 (Annals of Computer Science and Information Systems 18)
ISBN: 978-1-5386-8005-6
ISBN: 978-83-952357-8-8
Federated Conference on Computer Science and Information Systems (FedCSIS) <2019, Leipzig>
Fraunhofer SCAI ()

Context is widely considered for NLP and knowledge discovery since it highly influences the exact meaning of natural language. The scientific challenge is not only to extract such context data, but also to store this data for further NLP approaches. Here, we propose a multiple step knowledge graphbased approach to utilize context data for NLP and knowledge expression and extraction. We introduce the graph-theoretic foundation for a general context concept within semantic networks and show a proof-of-concept-based on biomedical literature and text mining. We discuss the impact of this novel approach on text analysis, various forms of text recognition and knowledge extraction and retrieval.